Working with Amazon EC2 Auto Scaling Groups and Network Load Balancer
The hands-on lab is part of these learning pathsSee 2 more
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This is a long-running lab that you can pause for up to 1 hour
up to 1h
This lab introduces the basics of Auto Scaling in Amazon Web Services. The Amazon Web Services (AWS) Auto Scaling service automatically adds or removes compute resources allocated for your cloud application, in response to changes in demand. For applications configured to run on a cloud infrastructure, scaling is an important part of cost control and resource management.
Scaling is the ability to increase or decrease the compute capacity of your application either by changing the number of servers (horizontal scaling) or by changing the size of the servers (vertical scaling).
Auto Scaling helps you maintain application availability and allows you to scale your Amazon EC2 capacity up or down automatically according to the defined conditions. You can use Auto Scaling to help ensure that you are running your desired number of Amazon EC2 instances. Auto Scaling can also automatically increase the number of Amazon EC2 instances during demand spikes to maintain performance and decrease capacity during lulls to reduce costs. Auto Scaling is well suited to applications that have stable demand patterns, or that experience hourly, daily, or weekly variability in usage.
In this lab, you will create an Auto Scaling Group and place it behind a Network Load Balancing (NLB). Don't worry if you don't fully understand all the components yet. Each one will be discussed in greater detail as you create and configure them. At the end of this lab you will have an Auto Scaling Group with several web server instances behind a Network Load Balancer.
Upon completion of this lab you will be able to:
- Configure Auto Scaling to automatically launch EC2 instances using conditions described by CloudWatch alarms
- Create and configure a Network Load Balancer
- Utilize Auto Scaling and a Network Load Balancer to ensure the availability of compute resources
- Build an elastic cluster by integrating Auto Scaling with an Elastic Load Balancer
- Perform end-to-end testing of the system and understand how to diagnose issues
Although this is a beginner-level lab, you should be familiar with AWS basics including:
- Using the AWS Management Console
- EC2 (launching an instance, connecting to an instance via SSH)
- Conceptual understanding of CloudWatch, and EC2 Security Groups (firewall rules)
January 6th, 2023 - Updated the instructions and screenshots to reflect the latest UI
May 16, 2022 - Updated the instructions and screenshots to reflect the latest UI
January 17th, 2022 - Updated the instructions and screenshots to reflect the latest UI
October 12th, 2021 - Updated screenshots to reflect the latest user-interface changes
September 9th, 2021 - Clarified an instruction when creating the target group
September 7th, 2021 - Added required TCP instructions for Target Groups display issue
June 16th, 2021 - Minor updates to load balancer creation instructions
June 3rd, 2021 - Updated the load balancer creation instructions to reflect the new console workflow
August 27th, 2020 - Updated screenshots to reflect the EC2 instances user interface
July 10th, 2020 - Updated all instructions and screenshots
June 24th, 2019 - Updated the instructions to mention the new UDP support for NLBs
April 26th, 2019 - Updated the commands used to install the
March 14th, 2019 - Modified the lab to use launch configuration rather than launch template to avoid misconfiguration issues
March 5th, 2019 - Updated the lab to use a Network Load Balancer and launch template and improved instruction clarity. A lab using a Classic Elastic Load Balancer, Launch Configurations, and Simple Notification Service is available here.
March 3rd, 2019 - Added a customized validation lab Step
March 1st, 2019 - Updated environment diagrams to the latest AWS icon library
January 10th, 2019 - Added a validation lab Step to check the work you perform in the lab
September 10, 2018 - Updated instructions and images to improve the lab experience
Andrew is a Labs Developer with previous experience in the Internet Service Provider, Audio Streaming, and CryptoCurrency industries. He has also been a DevOps Engineer and enjoys working with CI/CD and Kubernetes.
He holds multiple AWS certifications including Solutions Architect Associate and Professional.